SoulX-Singer: Towards High-Quality Zero-Shot Singing Voice Synthesis
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Abstract (arXiv)
While recent years have witnessed rapid progress in speech synthesis, open-source singing voice synthesis (SVS) systems still face significant barriers to industrial deployment, particularly in terms of robustness and zero-shot generalization. In this report, we introduce SoulX-Singer, a high-quality open-source SVS system designed with practical deployment considerations in mind. SoulX-Singer supports controllable singing generation conditioned on either symbolic musical scores (MIDI) or melodic representations, enabling flexible and expressive control in real-world production workflows. Trained on more than 42,000 hours of vocal data, the system supports Mandarin Chinese, English, and Cantonese and consistently achieves state-of-the-art synthesis quality across languages under diverse musical conditions. Furthermore, to enable reliable evaluation of zero-shot SVS performance in practical scenarios, we construct SoulX-Singer-Eval, a dedicated benchmark with strict training-test disentanglement, facilitating systematic assessment in zero-shot settings.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 31 of its 34 references that are in the map. First posted on arXiv 8 Feb 2026.
Builds on
31 of 34 references.
References · 31
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19 more
- 2025IndexTTS2: A Breakthrough in Emotionally Expressive and Duration-Controlled Auto-Regressive Zero-Shot Text-to-Speechcited by 85
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Built on by
Citing papers per year: 2026: 3.
3 papers.
- 2026VocalParse: Towards Unified and Scalable Singing Voice Transcription with Large Audio Language Modelscited by 0
- 2026VocalRender: Score-Native Singing Voice Synthesis for Real-World Compositioncited by 0
- 2026TUTTI: Toward generalizable audio-to-score transcription via fully synthesized datacited by 0
- 2026TUTTI: Toward generalizable audio-to-score transcription via fully synthesized data1 Sep 2026
- 2026VocalRender: Score-Native Singing Voice Synthesis for Real-World Composition30 Jul 2026
- 2026VocalParse: Towards Unified and Scalable Singing Voice Transcription with Large Audio Language Models6 May 2026